Global Satellite View Revealing

By Louise S. Durham

Every picture tells a different story: From left to right, a Landsat (satellite) image of the Caicos Platform, one of the areas used in the ExxonMobil study; a classified image of the same platform created using statistics-based algorithms that bin individual pixels into statistically similar clusters; and an interpreted facies map that has been calibrated to sediment data collected in the field.

All potential reservoir rocks have their own extraordinary characteristics, along with various quirks that must be evaluated before embarking on an exploration program.

Carbonates are no exception.

Accurate characterization of carbonate reservoirs can be tedious in that it requires an understanding of the variability and lateral distribution of the carbonate sediments.

Remote sensing techniques may provide an efficient means for understanding lateral facies variability in modern carbonate environments and, in turn, ancient carbonate reservoirs, according to AAPG member Steve Kaczmarek, senior geoscientist at ExxonMobil Upstream Research Company.

Kaczmarek was one of six authors who presented a poster on the subject, “Global Satellite Facies Mapping: Modern Carbonates Revealed!” at the recent AAPG Annual Convention in Denver. His co-authors, all AAPG members who also are with ExxonMobil, were Melissa Hicks, Shawn Fullmer, Kelley Steffen, Tabitha Hensley and Lizbeth Miles.

“A big issue with field programs undertaken to generate facies maps,” Kaczmarek said, “is they can encounter logistical issues in addition to being time and resource intensive.”

He pointed out that carbonate depositional settings are well suited for remote sensing work because carbonates generally thrive in shallow, relatively clear water – a necessity for satellite data acquisition in sub-aqueous environments.

“Prediction of facies distributions in ancient carbonate rocks is essential for accurate evaluation of reservoir-scale heterogeneity and even identification of exploration-scale fairways,” Kaczmarek said.

“Creation of new high-resolution facies maps has led to a better understanding of sediment distribution and biotic variations within modern carbonate systems.”

Global Research

Regions included in the ExxonMobil study are:

Little Bahamas Bank.

Great Bahamas Bank.

The Caicos Islands (BWI).

Cocos (Keeling) Islands.

Glovers and Chinchorro (Belize).

The Maldives.

Australia’s Great Barrier Reef.

Parts of the Arabian Gulf, Red Sea and Southeast Asia.

“We specifically focused on mapping modern carbonates in a variety of structural, climatic and hydrodynamic regimes,” Kaczmarek said. “As a result, the study includes isolated platforms, attached rims and ramps that are in macrotidal and microtidal regimes and tropical, subtropical and arid climates.”

“Study regions also represent active and passive margins, open ocean settings and marginal seas,” he added.

Kaczmarek noted this technology has been used before in different capacities, but it’s the first time it’s been used in this kind of investigation over large carbonate platforms.

“This project is global in scope,” he said, “and that really sets it apart from a lot of other satellite-based research being done now.”

First Separate, Then Define

An abbreviated blueprint reveals the basics of this technology application.

Step 1 in the quest to get a better handle on just how sediments are distributed in modern carbonate reservoirs entailed harnessing Landsat data and using statistics-based algorithms that bin, or group, pixels in each Landsat image into specific clusters. Each pixel in an image is put into a specific bin or cluster based on its spectral response.

“Statistically, what we’re trying to do is separate all pixels in an image into bins,” Kaczmarek said. “The difference between bins is maximized, and the difference between pixels within a bin is minimized, so pixels within a single bin are more similar to other pixels in that bin than pixels in a different bin.”

“Where we have it available, we condition those thematic maps with field-collected sediment data from these different platforms,” Kaczmarek said. “This allows us to extrapolate away from where we have data.

“For example, if you have one data point in each bin you can classify every bin in your image and give it a sediment type,” he noted. “From there we make different comparisons.”

Practical Applications

In addition to sers instructional aids, the maps provide the geoscientists with modern analogs.

Kaczmarek noted, for instance, that they have a group of pictures of images from different size platforms from around the world that they can use to compare to subsurface reservoirs. He mentioned the images are used to generate rule sets for predicting how facies could be distributed in ancient reservoirs.

They also use the maps to try to better understand the controls on how the sediments are distributed on modern platforms. This is doable because they know what the modern constraints are, such as climate, currents, waves and wind.

Additionally, the images are used to provide constraint on the level of complexity within the different depositional environments.

“This work has allowed us to see a lot smaller scale heterogeneity in these systems,” Kaczmarek said. “That has implications when you’re trying to constrain the level of complexity, or the complexity or precision of how facies are distributed in geologic models, for instance.”

He cautioned that with any remote sensing work data quality is paramount, adding that newer data tend to be somewhat better. He also noted the data can be compromised by certain weather conditions over a platform during a data satellite flyover.